John M. Abowd

John Maron Abowd (born December 22, 1951) is an American economist who has served as the Edmund Ezra Day Professor Emeritus of Economics, Statistics, and Data Science since 2021. From 2016 to 2022, he served as Associate Director for Research and Methodology and Chief Scientist at the United States Census Bureau. Abowd is best known for his contributions in the field of labor economics, and in particular his work in creating, disseminating, and using longitudinal employee-employer matched data.

Career

Abowd received a BA in economics (with highest honors) from the University of Notre Dame in 1973 and a PhD in economics from the University of Chicago in 1977, under supervision of Arnold Zellner.

Prior to arriving at Cornell University in 1987, Abowd served on the faculty at Princeton University, the University of Chicago, and the Massachusetts Institute of Technology. In 2014, he was elected a Fellow of the Econometric Society.

Abowd served as President of the Society of Labor Economists in 2014. He was chair in 2013 for the Business and Economic Statistics Section and fellow of the American Statistical Association. He is an elected member of the International Statistical Institute (2012). Abowd served as a distinguished senior research fellow at the United States Census Bureau from 1998 to 2012. He also served on the National Academies' Committee on National Statistics from 2010 to 2013 and as director of the Cornell Institute for Social and Economic Research (CISER) from 1999 to 2007.

Abowd, along with John Haltiwanger and Julia Lane, received the 2014 Roger Herriot Award from the American Statistical Association for work improving federal data collection, and in particular work developing and disseminating employee-employer matched data through the Census Bureau's LEHD Program.

Current research

Abowd's current research focuses on the creation, dissemination, privacy protection, and use of matched longitudinal data on employers and employees. Abowd helped to found and continues to provide scientific leadership for the U.S. Census Bureau's Longitudinal Employer-Household Dynamics Program, which integrates censuses, demographic surveys, economic surveys, and administrative data to produce research and public-use data.

Abowd's other research interests include network models for integrated labor market data; statistical methods for confidentiality protection of microdata, including the creation of synthetic data; international comparisons of labor market outcomes; executive compensation; bargaining and other wage-setting institutions; and the econometric tools of labor market analysis. in which Abowd, Francis Kramarz, and David Margolis used a matched sample of French employees and employers to decompose annual compensation into components related to observable employee characteristics, personal heterogeneity, firm heterogeneity, and residual variation. Their econometric approach, now widely referred to as the "AKM decomposition," laid the groundwork for a large body of subsequent research using employee-employer linked data in labor economics to understand topics including inter-industry wage differentials, firm size-wage effects, and job search and matching in the labor market.

In other widely cited work with David Card, Abowd used longitudinal data to analyze changes in individual earnings and hours over time. Abowd and Card explored the covariance structure of earnings and hours and interpreted them in the context of a life-cycle model of labor supply.

Abowd also has written extensively on executive compensation, and in particular on whether performance-based compensation affects corporate performance.